hubert-base-timit-demo-google-colab-ft30ep_v5

danieleV9H/hubert-base-timit-demo-google-colab-ft30ep_v5

hubert-base-timit-demo-google-colab-ft30ep_v5 is a automatic speech recognition model from danieleV9H. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: hubert
Access: Public
Created: May 12, 2022
Updated: May 14, 2022
SHA: b3aadc14

Model card

From the Hugging Face model README

hubert-base-timit-demo-google-colab-ft30ep_v5

This model is a fine-tuned version of facebook/hubert-base-ls960 on the timit-asr dataset. It achieves the following results on the evaluation set:

Loss: 0.4763
Wer: 0.3322

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.9596	0.87	500	3.1237	1.0
2.5388	1.73	1000	1.1689	0.9184
1.0448	2.6	1500	0.6106	0.5878
0.6793	3.46	2000	0.4912	0.5200
0.5234	4.33	2500	0.4529	0.4798
0.4368	5.19	3000	0.4239	0.4543
0.3839	6.06	3500	0.4326	0.4339
0.3315	6.92	4000	0.4265	0.4173
0.2878	7.79	4500	0.4304	0.4068
0.25	8.65	5000	0.4130	0.3940
0.242	9.52	5500	0.4310	0.3938
0.2182	10.38	6000	0.4204	0.3843
0.2063	11.25	6500	0.4449	0.3816
0.2099	12.11	7000	0.4016	0.3681
0.1795	12.98	7500	0.4027	0.3647
0.1604	13.84	8000	0.4294	0.3664
0.1683	14.71	8500	0.4412	0.3661
0.1452	15.57	9000	0.4484	0.3588
0.1491	16.44	9500	0.4508	0.3515
0.1388	17.3	10000	0.4240	0.3518
0.1399	18.17	10500	0.4605	0.3513
0.1265	19.03	11000	0.4412	0.3485
0.1137	19.9	11500	0.4520	0.3467
0.106	20.76	12000	0.4873	0.3426
0.1243	21.63	12500	0.4456	0.3396
0.1055	22.49	13000	0.4819	0.3406
0.1124	23.36	13500	0.4613	0.3391
0.1064	24.22	14000	0.4842	0.3430
0.0875	25.09	14500	0.4661	0.3348
0.086	25.95	15000	0.4724	0.3371
0.0842	26.82	15500	0.4982	0.3381
0.0834	27.68	16000	0.4856	0.3337
0.0918	28.55	16500	0.4783	0.3344
0.0773	29.41	17000	0.4763	0.3322

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 1.18.3
Tokenizers 0.12.1

Task: Automatic Speech Recognition
Library: transformers
Type: hubert
License: apache-2.0
Created: May 12, 2022
Updated: May 14, 2022